A ubiquitous technique to manage communication cost in power or bandwidth limited systems is event-triggered (ET) estimation [1]}, [2]}, [3]}, [4]}, where communication is limited to only situations where the information is deemed useful. This typically takes the form of a threshold on some useful quantity, like the Kalman Filter (KF) innovation [2]}, [3]}, [4]}. ET allows the user to lower resource consumption by changing this threshold, thus reducing the volume of transmitted information and trading off estimation accuracy with resource use. Ref. [8]} introduces a method that guarantees the trade-off is optimal by accounting for both task performance and resources. While providing a very comprehensive Pareto Front solution, the methods do not include any path or motion planning, and require heavy computation power, resulting in lengthy computation times and precluding onboard implementation.
